Operation bagging management system and method capable of intelligently controlling sorting and automatically packaging

Abstract

The invention provides an operation package management system and method for intelligently controlling sorting and automatic packaging, and the system comprises a standard configuration matching module which is used for automatically matching package standard configuration according to an input operation demand; the sorting module is used for controlling the intelligent sorting execution structure to sort the required consumables according to the bagging standard configuration; and the packaging module is used for automatically packaging the required consumables after the required consumables are sorted. According to the operation package management system and method capable of intelligently controlling sorting and automatic packaging, the package standard configuration is automatically matched based on the input operation requirement, the intelligent sorting execution structure is scheduled according to the package standard configuration to sort the required consumables and automatically package the consumables, the packaging efficiency of the operation package is improved, and meanwhile, the packaging efficiency of the operation package is improved. The automatic packaging device is suitable for automatic packaging of different consumables of various operation types, and packaging is more flexible.

Description

Technical Field

[0001] The present invention relates to the technical field of material sorting, and in particular to a surgical kit management system and method for intelligently controlling sorting and automatically packing. Background Art

[0002] Currently, surgical consumables required in hospitals are typically pre-packaged manually into surgical kits. Traditional processes rely heavily on manual selection, placement, and packaging based on kit lists. There are numerous different types of kits for different surgical procedures, and manual identification and manipulation can easily lead to omissions and mis-packaging, potentially causing shortages or waste during surgery. Furthermore, most automated solutions currently available on the market are standard logistics packaging equipment, which is only suitable for large, uniformly sized, and single-item items. They are unable to cope with the complex, small, delicate, and batch-sensitive nature of surgical consumables, nor do they have the ability to switch between multiple categories at high speed and flexibly package them.

[0003] In view of this, there is an urgent need for a surgical kit management system and method with intelligent control sorting and automatic packaging to at least solve the above-mentioned deficiencies. Summary of the Invention

[0004] One of the purposes of the present invention is to provide a surgical kit management system and method with intelligent control sorting and automatic packaging. The system automatically matches the standard configuration of the kit based on the input surgical requirements, and schedules the intelligent sorting execution structure to sort the required consumables and automatically pack them according to the standard configuration of the kit, thereby improving the packaging efficiency of the surgical kit. At the same time, it is suitable for the automatic packaging of different consumables for various types of surgeries, making packaging more flexible.

[0005] The surgical kit management system with intelligent control sorting and automatic packaging provided by the embodiment of the present invention includes:

[0006] Standard configuration matching module, used to automatically match the standard configuration of the package according to the input surgical requirements;

[0007] Sorting module, used to control the intelligent sorting execution structure to sort the required consumables according to the standard configuration of the package;

[0008] The packing module is used to automatically pack the required consumables after the required consumables are sorted.

[0009] The surgical kit management system with intelligent control sorting and automatic packaging provided by the embodiment of the present invention also includes:

[0010] The storage condition monitoring module is used to verify the storage standardization of inventory consumables based on the preset storage conditions of the inventory consumables and the real-time perception of the environmental status of the inventory consumables.

[0011] The surgical kit management system with intelligent control sorting and automatic packaging provided by the embodiment of the present invention also includes:

[0012] The linkage module is used to link with the hospital information system to obtain surgery scheduling information and generate an input surgery demand waiting sequence based on the surgery scheduling information.

[0013] The surgical kit management system with intelligent control sorting and automatic packaging provided by the embodiment of the present invention also includes:

[0014] The docking module is used to connect to the intelligent delivery robot to deliver the packaged surgical kits.

[0015] Preferably, the docking module docks with the intelligent delivery robot to deliver the packaged surgical kit, including:

[0016] When the intelligent delivery robot performs the assigned task, it determines the assigned tasks to be taken over on the route;

[0017] Determine a point to be planned on the second remaining path of the assigned task to be taken over;

[0018] Plan the return path and return point of the planned point back to the first remaining path of the assigned task;

[0019] Calculate the time saved based on the distance between the return point and the starting point of the first remaining path;

[0020] Calculate the first delay duration based on the task transfer duration, the regression path length, and the path length from the point to be planned to the starting point of the second remaining path;

[0021] If the sum of the saved time and the first redundant time is greater than or equal to the first delay time, the to-be-planned point farthest from the starting point of the second remaining path among the corresponding to-be-planned points is used as the target planning point;

[0022] Control the intelligent delivery robot to temporarily take over the assigned task to be taken over and move along the second remaining path to the target planning point. After the intelligent delivery robot reaches the target planning point, it reissues the task to be taken over and returns to the regression point associated with the target planning point on the first remaining path.

[0023] Preferably, the docking module docks with the intelligent delivery robot to deliver the packaged surgical kit, and further includes:

[0024] If the sum of the saved time and the first redundant time is less than the first delay time, and the preset risk value of the type of surgery corresponding to the task to be taken over is greater than or equal to the preset risk value threshold, the delay time tolerance is determined based on the risk difference between the assigned task and the task to be taken over;

[0025] Determine the first target robot within the preset target range of the intelligent delivery robot to take over the assigned task;

[0026] Scheduling the transfer of the auxiliary task of the first target robot according to the time attribute information of the first target robot, and determining the auxiliary time balance;

[0027] The current first delay duration is updated based on the auxiliary duration balance and the delay duration tolerance to obtain a second delay duration. The sum of the delay durations is compared with the second delay duration. If the sum of the delay durations is greater than or equal to the second delay duration, it is determined whether there is a point to be planned located at the task endpoint of the task to be taken over.

[0028] If it exists, then the corresponding auxiliary transfer and takeover of the assigned tasks to be taken over will be carried out;

[0029] If it does not exist, dispatch the delivery personnel to carry out the assigned tasks to be taken over.

[0030] Preferably, the docking module schedules the first target robot to assist in task transfer according to the time attribute information of the first target robot, including:

[0031] The second redundant duration with the longest duration for the first target robot is used as the third redundant duration;

[0032] Determine a target time interval based on the third redundant time interval, and allocate a first time module corresponding to the second redundant time interval remaining after the third redundant time interval within the target time interval; wherein the length of a side of the first time module parallel to the target time interval is equal to the second redundant time interval, and the length of a side perpendicular to the target time interval is a unit length;

[0033] During allocation, the first duration module is allocated layer by layer, with the first duration module of each layer just filling the target time interval as the first priority allocation target;

[0034] If the first priority allocation target cannot be achieved, the second priority allocation target is to use the first duration module of each layer to fill the target time interval with the smallest time gap.

[0035] The remaining unallocated first duration modules after the n-th allocation layer is allocated based on the second priority allocation target are used as the second duration modules, where n is a natural number greater than 0;

[0036] Determine the total duration corresponding to the second duration module;

[0037] If the total duration is less than the third redundant duration, determining that the second duration module whose length exceeds the minimum length of the time gap is the third duration module;

[0038] Align the end of the third duration module with the end of the target time interval;

[0039] Connect the first portions of the remaining second duration modules except the third duration module in the second duration module to form a fourth duration module, and align the fourth duration module with the top of the target time interval;

[0040] If the total duration is greater than or equal to the third redundant duration, the first priority allocation target is the second duration module of each layer that just fills the target time interval after the n+1th layer;

[0041] The intervention timing of the first target robot-assisted task transfer is determined based on the allocation situation of each allocation layer, and the corresponding first target robot is scheduled to intervene in the auxiliary task transfer.

[0042] The embodiment of the present invention provides a surgical kit management method with intelligent control sorting and automatic packaging, including:

[0043] Step 1: Automatically match the standard configuration of the package based on the input surgical requirements;

[0044] Step 2: Control the intelligent sorting execution structure to sort the consumables required according to the standard configuration of the package;

[0045] Step 3: After the required consumables are sorted, they are automatically packaged.

[0046] The beneficial effects of the present invention are:

[0047] The present invention automatically matches the standard configuration of the package based on the input surgical requirements, and dispatches the intelligent sorting execution structure according to the standard configuration of the package to sort the required consumables and automatically pack them, thereby improving the packing efficiency of the surgical package. At the same time, it is suitable for the automatic packaging of different consumables for various types of surgeries, and the packaging is more flexible.

[0048] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in this application document.

[0049] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0051] Figure 1 Schematic diagram of a surgical kit management system with intelligent control sorting and automatic packaging according to an embodiment of the present invention;

[0052] Figure 2 Schematic diagram of a surgical kit management method with intelligent control sorting and automatic packaging in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0054] The embodiment of the present invention provides a surgical kit management system with intelligent control sorting and automatic packaging, such as Figure 1 As shown, including:

[0055] Standard configuration matching module 1, used to automatically match the standard configuration of the package according to the input surgical requirements;

[0056] Sorting module 2, used to control the intelligent sorting execution structure to sort the required consumables according to the package standard configuration;

[0057] Packing module 3, used for automatically packing the required consumables after the required consumables are sorted;

[0058] The surgical kit management system with intelligent control sorting and automatic packaging also includes:

[0059] The storage condition monitoring module is used to verify the storage standardization of inventory consumables based on the preset storage conditions of inventory consumables and the real-time environmental status of inventory consumables;

[0060] The linkage module is used to link with the hospital information system to obtain surgery scheduling information and generate a waiting sequence for input surgery requirements based on the surgery scheduling information;

[0061] The docking module is used to connect to the intelligent delivery robot to deliver the packaged surgical kits.

[0062] In this embodiment, the input surgical requirement is the surgical requirement that currently requires a surgical kit; when obtaining the input surgical requirement, each surgery corresponds to the time required for a surgical kit. When the current time reaches the time required for the surgical kit, the surgical requirement corresponding to the surgery is the input surgical requirement.

[0063] In this embodiment, the standard configuration of the package is: the standard configuration of the consumables required for the operation corresponding to the input operation requirements, and the standard configuration of the consumables required for each operation is manually preset.

[0064] In this embodiment, the intelligent sorting execution structure is: a crawler-type cargo lane sorting device and a multi-link cargo lane sorting device.

[0065] In this embodiment, the required consumables are the consumables recorded in the standard configuration of the kit.

[0066] In this embodiment, the hospital information system includes: HIS, SPD and other information platforms; linkage means that the surgical kit management system is compatible with and communicates with these information platforms.

[0067] In this embodiment, the preset storage conditions for the inventory consumables are determined according to the types of inventory consumables, such as: temperature and humidity conditions suitable for the storage of dressings, and temperature and humidity conditions suitable for the storage of certain biological reagents.

[0068] In this embodiment, when verifying the preservation standardization, if the environment status does not meet the preservation condition, the verification fails; otherwise, the verification passes.

[0069] In this embodiment, the surgery scheduling information includes: surgery type and surgery time.

[0070] In this embodiment, the surgical requirement waiting sequence is input to sort the surgical requirements in the surgical scheduling information in the order of the time required for their corresponding surgical packages. The time required for the surgical package is a preset time before the surgical time of the corresponding surgery. The preset time is manually set in advance, for example: 10 minutes.

[0071] The working principle and beneficial effects of the above technical solution are:

[0072] The present invention automatically matches the corresponding standard configuration of the package based on the name of the surgery or the classification of the procedure, realizes a one-click intelligent packaging process, reduces the complexity of personnel operation, and supports customization and dynamic switching of surgical types. The temperature and humidity monitoring module is integrated into the equipment to sense the status of the consumables storage environment in real time, ensuring the safety and compliance of the use of medical consumables that are sensitive to storage conditions (such as dressings, syringes, biological reagents, etc.). It is seamlessly integrated with the hospital's existing HIS, SPD and other core information platforms, and automatically generates corresponding surgical package pre-packaging tasks based on surgical scheduling information, realizing closed-loop data management of the entire process of consumables from warehouse application, automatic sorting and packaging, and real-time inventory updates. In addition, the system also reserves a standard communication interface, which can be connected to the intelligent distribution robot or rail transportation system in the hospital, supports automatic triggering of distribution tasks after packaging is completed, and accurately delivers the surgical package to the designated operating room, further improving the intelligence and automation level of consumables preparation and distribution, and comprehensively improving the hospital's material management efficiency and surgical response capabilities.

[0073] The present invention automatically matches the standard configuration of the package based on the input surgical requirements, and dispatches the intelligent sorting execution structure according to the standard configuration of the package to sort the required consumables and automatically pack them, thereby improving the packing efficiency of the surgical package. At the same time, it is suitable for the automatic packaging of different consumables for various types of surgeries, and the packaging is more flexible.

[0074] In one embodiment, the docking module docks with the intelligent delivery robot to deliver the packaged surgical kit, including:

[0075] When the intelligent delivery robot performs the assigned task, it determines the assigned tasks to be taken over on the route;

[0076] Determine a point to be planned on the second remaining path of the assigned task to be taken over;

[0077] Plan the return path and return point of the planned point back to the first remaining path of the assigned task;

[0078] Calculate the time saved based on the distance between the return point and the starting point of the first remaining path;

[0079] Calculate the first delay duration based on the task transfer duration, the regression path length, and the path length from the point to be planned to the starting point of the second remaining path;

[0080] If the sum of the saved time and the first redundant time is greater than or equal to the first delay time, the to-be-planned point farthest from the starting point of the second remaining path among the corresponding to-be-planned points is used as the target planning point;

[0081] Control the intelligent delivery robot to temporarily take over the assigned task to be taken over and move along the second remaining path to the target planning point. After the intelligent delivery robot reaches the target planning point, it reissues the task to be taken over and returns to the regression point associated with the target planning point on the first remaining path.

[0082] In this embodiment, the assigned task is that the intelligent delivery robot delivers the packaged surgical kit to the operating room, for example: the intelligent delivery robot A delivers surgical kit a to the operating room 1.

[0083] In this embodiment, the task to be taken over is the task of which surgical package the faulty intelligent delivery robot needs to deliver to which operating room, for example: the faulty delivery robot B needs to deliver surgical package b to operating room 2.

[0084] In this embodiment, the second remaining path is a route from the location of the delivery machine with a route failure to the corresponding operating room to be taken over the distribution task.

[0085] In this embodiment, the points to be planned may be determined randomly or according to manually set planning rules (for example, selecting a point to be planned every 5 meters).

[0086] In this embodiment, when planning the regression path and regression point of the point to be planned back to the first remaining path of the assigned task, planning is performed based on path planning technology and the distribution site map; the regression path is the route from the point to be planned to the second remaining path; the regression point is the intersection of the regression path and the first remaining path.

[0087] In this embodiment, the time saved is obtained by dividing the path length from the regression point to the starting point of the first remaining path by the travel speed of the delivery robot.

[0088] In this embodiment, the redundant time is: the time difference between the expected completion time of the intelligent delivery robot to immediately complete its assigned task and the specified time for completing its assigned task at the latest. The expected completion time is before the specified time. The first redundant time represents the redundant time corresponding to the intelligent delivery robot that is waiting to take over the assigned task.

[0089] In this embodiment, the first delay duration is obtained by dividing the sum of the regression path length and the path length from the point to be planned to the starting point of the second remaining path by the travel speed of the delivery robot and adding the task transfer duration. The task transfer duration is, for example: the total time spent by the intelligent delivery robot A to pick up the surgical kit b and place the surgical kit b.

[0090] In this embodiment, if the sum of the saved time and the first redundant time is greater than or equal to the first delay time, it means that the intelligent delivery robot temporarily takes over the distribution task to be taken over (for example: the intelligent delivery robot A helps the intelligent delivery robot B to carry the surgical kit b to its destination) will not cause delays in the distribution task it itself is performing, and the target planning point is selected from the corresponding points to be planned; when selecting, the closer to the destination, the shorter the distance that other robots will help to continue the distribution, therefore, the corresponding point to be planned that is farthest from the starting point of the second remaining path is used as the target planning point.

[0091] In this embodiment, reissuing the task to be taken over is: the intelligent delivery robot places the surgical kit collection box corresponding to the temporarily taken over distribution task to be taken over at the target planning point.

[0092] In this embodiment, the regression point associated with the target planning point on the first remaining path is: the intersection of the planned regression path corresponding to the target planning point and the second remaining path.

[0093] The working principle and beneficial effects of the above technical solution are:

[0094] The intelligent delivery robot may malfunction while performing its assigned tasks, which will cause delays in the delivery of the corresponding surgical kits and thus delay the surgical process.

[0095] When the intelligent delivery robot performs the distribution task, the present invention controls it to perform machine vision scanning along the way, determines the surgical package material frame placed after the faulty intelligent delivery robot or other intelligent delivery robot temporarily takes over, matches the position with the task location in the queue of distribution tasks to be taken over, and determines the distribution tasks to be taken over on the route (that is, which operating room the surgical package on the route needs to be delivered to).

[0096] After determining the task to be taken over, since the intelligent delivery robot has its own tasks, in order not to cause delays in its own tasks, it is necessary to measure the transportation distance that the intelligent delivery robot can help deliver the surgical kits. Therefore, the to-be-planned point on the second remaining path of the task to be taken over is determined. The to-be-planned point is the end point where the intelligent delivery robot to be selected considers helping to deliver the surgical kit corresponding to the task to be taken over. After the preliminary selection, it is necessary to further plan the route (return path) and return point on the first remaining path.

[0097] Next, the previously selected points to be planned are selected. The path length from the return point to the starting point of the first remaining path is the path length that the intelligent delivery robot avoids on the initially planned first remaining path after assisting in delivery and then returning to the first remaining path. The time saved by this path length can be calculated based on the path length from the return point to the starting point of the first remaining path and the delivery robot's travel speed. Task transfer (for example, transferring the surgical set material frame of a faulty robot to the intelligent delivery robot assisting in transfer), travel on the return path, and travel on the path from the point to be planned to the starting point of the second remaining path will all cause delays in the delivery time of the intelligent delivery robot assisting in transfer. Therefore, the first delay time is calculated based on the task transfer time, the return path length, and the path length from the point to be planned to the starting point of the second remaining path. The sum of the time is the sum of the saved time and the first redundant time. If the sum of the time is greater than or equal to the first delay time, the remaining time is sufficient to support the completion of the auxiliary transfer. The point to be planned that meets the requirements and is farthest from the starting point of the second remaining path is determined as the target planning point.

[0098] Finally, the intelligent delivery robot is controlled to transfer the surgical kit that requires assisted transfer and proceed along the second remaining path to the target planning point. After the intelligent delivery robot arrives at the target planning point, it places the assisted transferred surgical kit and its container at the target planning point. Based on the target planning point location, the contents of the assisted transferred surgical kit, and the operating room it is being delivered to, a new pending task is generated and stored in the pending task queue. This new pending task awaits takeover by the intelligent delivery robot on the new route.

[0099] The present invention enables the intelligent delivery robot to take over other distribution tasks that require auxiliary distribution while performing its own tasks. The auxiliary delivery robot uses its own redundant resources to take over the surgical packages corresponding to the distribution tasks to be taken over in the route without affecting its own distribution tasks, thereby greatly improving the utilization rate of distribution resources.

[0100] In one embodiment, the docking module docks with the intelligent delivery robot to deliver the packaged surgical kit, and further includes:

[0101] If the sum of the saved time and the first redundant time is less than the first delay time, and the preset risk value of the type of surgery corresponding to the task to be taken over is greater than or equal to the preset risk value threshold, the delay time tolerance is determined based on the risk difference between the assigned task and the task to be taken over;

[0102] Determine the first target robot within the preset target range of the intelligent delivery robot to take over the assigned task;

[0103] Scheduling the transfer of the auxiliary task of the first target robot according to the time attribute information of the first target robot, and determining the auxiliary time balance;

[0104] The current first delay duration is updated based on the auxiliary duration balance and the delay duration tolerance to obtain a second delay duration. The sum of the delay durations is compared with the second delay duration. If the sum of the delay durations is greater than or equal to the second delay duration, it is determined whether there is a point to be planned located at the task endpoint of the task to be taken over.

[0105] If it exists, then the corresponding auxiliary transfer and takeover of the assigned tasks to be taken over will be carried out;

[0106] If it does not exist, dispatch the delivery personnel to carry out the assigned tasks to be taken over.

[0107] In this embodiment, the risk difference refers to the difference in risk levels of the surgeries corresponding to the surgical packages assigned to the assigned task and the assigned task to be taken over.

[0108] In this embodiment, when determining the delay time tolerance, the higher the risk value of the surgery type corresponding to the assigned task to be taken over is than the risk value of the surgery type corresponding to the assigned task, the longer the delay time tolerance is.

[0109] In this embodiment, the first target robot is another intelligent delivery robot within the preset target range of the intelligent delivery robot that is about to take over the assigned task. The preset target range is, for example, within 3 meters around the intelligent delivery robot that is about to take over the assigned task, and is set manually according to needs.

[0110] In this embodiment, the time attribute information is: the time during which the first target robot can be used to assist the intelligent delivery robot that is to take over the assigned task to perform task transfer, such as: the redundant time of the first target robot.

[0111] In this embodiment, the assistance time balance is: the transfer time saved by transferring the first target robot-assisted task.

[0112] In this embodiment, the auxiliary duration balance, the delay duration tolerance, and the first delay duration are summed to obtain the second delay duration.

[0113] The working principle and beneficial effects of the above technical solution are:

[0114] If the sum of the durations is greater than or equal to the first delay duration, the surplus time cannot support the completion of the assisted transfer, and the preset risk value of the type of surgery corresponding to the assigned task to be taken over is greater than or equal to the preset risk value threshold, and it has the urgency of execution. At this time, the risk difference between the assigned task and the assigned task to be taken over is considered. The risk difference refers to the difference in the preset risk values ​​of the assigned task and the assigned task to be taken over for the corresponding types of surgery. The delay time tolerance of the main assigned task is determined based on the risk difference. For example: the risk value difference is the risk value corresponding to the assigned task to be taken over minus the risk value corresponding to the assigned task. When the risk value difference is less than or equal to 0, the delay time tolerance is 0; when the risk value difference is greater than 0, the risk value difference and the delay time tolerance satisfy a proportional relationship, and the specific proportional relationship is preset manually.

[0115] At the same time, considering that in this urgent situation, the transfer process may be delayed when the task transfer volume is large, the time saved by the first target robot assisting the intelligent delivery robot to take over the assigned task (the assistance time surplus) is determined based on the time (time attribute information) during which the first target robot can assist the intelligent delivery robot to take over the assigned task. The second delay time is obtained by summing the assistance time surplus, the delay time tolerance, and the first delay time.

[0116] In this critical situation, if the intelligent delivery robot has already relinquished the priority of its own assigned task, it makes sense to locate the planned point at the task endpoint of the task to be taken over. Otherwise, the robot would drop the surgical kit corresponding to the task to be taken over midway, and the kit would then have to wait for another robot to retrieve it. This is unreasonable. To ensure the necessary transfer behavior, the planned point at the task endpoint of the task to be taken over when the delay duration is greater than or equal to the second delay duration is set as the target planning point. Otherwise, the delivery personnel are urgently dispatched to make the distribution, which improves the rationality of the distribution.

[0117] In one embodiment, the docking module schedules the first target robot to transfer the assisted task according to the time attribute information of the first target robot, including:

[0118] The second redundant duration with the longest duration for the first target robot is used as the third redundant duration;

[0119] Determine a target time interval based on the third redundant time interval, and allocate a first time module corresponding to the second redundant time interval remaining after the third redundant time interval within the target time interval; wherein the length of a side of the first time module parallel to the target time interval is equal to the second redundant time interval, and the length of a side perpendicular to the target time interval is a unit length;

[0120] During allocation, the first duration module is allocated layer by layer, with the first duration module of each layer just filling the target time interval as the first priority allocation target;

[0121] If the priority allocation target cannot be achieved, the second priority allocation target is to use the first duration module of each layer to fill the target time interval with the smallest time gap.

[0122] The remaining unallocated first duration modules after the n-th allocation layer is allocated based on the second priority allocation target are used as the second duration modules, where n is a natural number greater than 0;

[0123] Determine the total duration corresponding to the second duration module;

[0124] If the total duration is less than the third redundant duration, determining that the second duration module whose length exceeds the minimum length of the time gap is the third duration module;

[0125] Align the end of the third duration module with the end of the target time interval;

[0126] Connect the first portions of the remaining second duration modules except the third duration module in the second duration module to form a fourth duration module, and align the fourth duration module with the top of the target time interval;

[0127] If the total duration is greater than or equal to the third redundant duration, the priority allocation target is to fill the target time interval with the second duration module of each layer after the n+1th layer.

[0128] The intervention timing of the first target robot-assisted task transfer is determined based on the allocation situation of each allocation layer, and the corresponding first target robot is scheduled to intervene in the auxiliary task transfer.

[0129] In this embodiment, the second redundant time length is the redundant time length of the first target robot.

[0130] In this embodiment, the target time interval is: a time interval with the third redundant time length as the interval length, the starting point of the time interval is the passage moment, and the first time length modules corresponding to other first target robots are allocated within the target time interval in order to allow as many first target robots as possible to simultaneously coordinate the auxiliary task transfer.

[0131] In this embodiment, the first duration module is allocated layer by layer in order to evenly and reasonably allocate the collaborative operation time period during the longest time of the collaborative switching so as not to cause congestion in the collaborative switching.

[0132] In this embodiment, the first duration module of each layer just filling up the target time interval indicates that the first target robot corresponding to the first duration module continues to assist without interruption.

[0133] In this embodiment, the minimum time gap is reserved in order to shorten the interruption duration of the connection assistance as much as possible.

[0134] In this embodiment, when the nth layer allocation layer is completed based on the second priority allocation target, a time gap will be formed at the end of the nth layer. When allocating the second duration module of the n+1 layer, it is necessary to prioritize allocating the second duration module above the time gap to avoid the formation of a time gap at the end of the n+1 layer again when the second duration module of the n+1 layer is insufficient for allocation at this layer, thereby resulting in insufficient number of first target robots corresponding to the time gap and low collaborative efficiency in the time period corresponding to the time gap. n is a natural number greater than 0.

[0135] In this embodiment, the comparison between the total duration corresponding to the second duration module and the third redundant duration is to determine whether the second duration module of the n+1th layer is sufficient for allocation to this layer. If the total duration is less than the third redundant duration, it means that it is insufficient for allocation to this layer; otherwise, it is sufficient for allocation to this layer.

[0136] In this embodiment, the third duration module is allocated to the second duration module preferentially above the time gap.

[0137] In this embodiment, the first priority allocation goal is to just fill the allocated allocation layer with the duration module.

[0138] In this embodiment, the second priority allocation goal is to minimize the time gap left when the allocated allocation layers are filled with the duration modules.

[0139] In this embodiment, after all the first duration modules are allocated, a perpendicular line is drawn between the two ends of the first duration module and the target time interval. The earlier moment in the time interval corresponding to the intersection of the perpendicular lines is the moment when the first target robot corresponding to the corresponding first duration module intervenes in the auxiliary task transfer, and the later moment in the time interval corresponding to the intersection of the perpendicular lines is the moment when the first target robot corresponding to the corresponding first duration module stops the auxiliary task transfer.

[0140] The working principle and beneficial effects of the above technical solution are:

[0141] When scheduling the first target robot for assisted task transfer, the present invention modularizes the second redundant duration of the first target robot to obtain the first duration module. At the same time, the target time interval corresponding to the longest second redundant duration is used as the maximum time interval for collaborative assisted task transfer, and the first duration module is allocated within this time interval. The first priority allocation target is to fill the allocated allocation layer with duration modules exactly, thereby improving the utilization rate of the first target robot's redundant time. The second priority allocation target is to minimize the time gap left when the allocated allocation layer is filled with duration modules, thereby minimizing the interruption of the assistance.

[0142] In addition, a specific analysis is made of the situation where a time gap is formed at the end of the nth layer after the nth layer allocation is completed based on the second priority allocation target. When allocating the second duration module of the n+1th layer, the second duration module is allocated first above the time gap to avoid the problem of a time gap being formed at the end of the n+1th layer again when the second duration module of the n+1th layer is insufficient for allocation at this layer, which leads to an insufficient number of first target robots working collaboratively at the time corresponding to the time gap and low collaborative efficiency during the time period corresponding to the time gap. Finally, after all the first duration modules are allocated, the intervention timing of the first target robot's assisted task transfer is determined based on the allocation situation of each allocation layer. The corresponding first target robot is scheduled to intervene in the assisted task transfer according to the intervention timing, which improves the rationality of the time allocation of the first target machine's intervention in the assisted task transfer and greatly improves the efficiency of the assigned task transfer.

[0143] The embodiment of the present invention provides a surgical kit management method with intelligent control sorting and automatic packaging, such as Figure 2 As shown, including:

[0144] Step 1: Automatically match the standard configuration of the package based on the input surgical requirements;

[0145] Step 2: Control the intelligent sorting execution structure to sort the consumables required according to the standard configuration of the package;

[0146] Step 3: After the required consumables are sorted, they are automatically packaged.

[0147] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. Intelligent control sorting and automatic packaging surgical kit management system, characterized by: include: Standard configuration matching module, used to automatically match the standard configuration of the package according to the input surgical requirements; Sorting module, used to control the intelligent sorting execution structure to sort the required consumables according to the standard configuration of the package; The packing module is used to automatically pack the required consumables after the required consumables are sorted.

2. The intelligent control sorting and automatic packaging surgical kit management system according to claim 1, characterized in that: Also includes: The storage condition monitoring module is used to verify the storage standardization of inventory consumables based on the preset storage conditions of the inventory consumables and the real-time perception of the environmental status of the inventory consumables.

3. The intelligent control sorting and automatic packaging surgical kit management system according to claim 1, characterized in that: Also includes: The linkage module is used to link with the hospital information system to obtain surgery scheduling information and generate an input surgery demand waiting sequence based on the surgery scheduling information.

4. The intelligent control sorting and automatic packaging surgical kit management system according to claim 1, characterized in that: Also includes: The docking module is used to connect to the intelligent delivery robot to deliver the packaged surgical kits.

5. The intelligent control sorting and automatic packaging surgical kit management system according to claim 4, characterized in that: The docking module connects to the intelligent delivery robot to deliver the packaged surgical kits, including: When the intelligent delivery robot performs the assigned task, it determines the assigned tasks to be taken over on the route; Determine a point to be planned on the second remaining path of the assigned task to be taken over; Plan the return path and return point of the planned point back to the first remaining path of the assigned task; Calculate the time saved based on the distance between the return point and the starting point of the first remaining path; Calculate the first delay duration based on the task transfer duration, the regression path length, and the path length from the point to be planned to the starting point of the second remaining path; If the sum of the saved time and the first redundant time is greater than or equal to the first delay time, the to-be-planned point farthest from the starting point of the second remaining path among the corresponding to-be-planned points is used as the target planning point; Control the intelligent delivery robot to temporarily take over the assigned task to be taken over and move along the second remaining path to the target planning point. After the intelligent delivery robot reaches the target planning point, it reissues the task to be taken over and returns to the regression point associated with the target planning point on the first remaining path.

6. The intelligent control sorting and automatic packaging surgical kit management system according to claim 5, characterized in that: The docking module connects to the intelligent delivery robot to deliver the packaged surgical kits, and also includes: If the sum of the saved time and the first redundant time is less than the first delay time, and the preset risk value of the type of surgery corresponding to the task to be taken over is greater than or equal to the preset risk value threshold, the delay time tolerance is determined based on the risk difference between the assigned task and the task to be taken over; Determine the first target robot within the preset target range of the intelligent delivery robot to take over the assigned task; Scheduling the transfer of the auxiliary task of the first target robot according to the time attribute information of the first target robot, and determining the auxiliary time balance; The current first delay duration is updated based on the auxiliary duration balance and the delay duration tolerance to obtain a second delay duration. The sum of the delay durations is compared with the second delay duration. If the sum of the delay durations is greater than or equal to the second delay duration, it is determined whether there is a point to be planned located at the task endpoint of the task to be taken over. If it exists, then the corresponding auxiliary transfer and takeover of the assigned tasks to be taken over will be carried out; If it does not exist, dispatch the delivery personnel to carry out the assigned tasks to be taken over.

7. The intelligent control sorting and automatic packaging surgical kit management system according to claim 6, characterized in that: The docking module schedules the first target robot to transfer the auxiliary task according to the time attribute information of the first target robot, including: The second redundant duration with the longest duration for the first target robot is used as the third redundant duration; Determine a target time interval based on the third redundant time interval, and allocate a first time module corresponding to the second redundant time interval remaining after the third redundant time interval within the target time interval; wherein the length of a side of the first time module parallel to the target time interval is equal to the second redundant time interval, and the length of a side perpendicular to the target time interval is a unit length; During allocation, the first duration module is allocated layer by layer, with the first duration module of each layer just filling the target time interval as the first priority allocation target; If the first priority allocation target cannot be achieved, the second priority allocation target is to use the first duration module of each layer to fill the target time interval with the smallest time gap. The remaining unallocated first duration modules after the n-th allocation layer is allocated based on the second priority allocation target are used as the second duration modules, where n is a natural number greater than 0; Determine the total duration corresponding to the second duration module; If the total duration is less than the third redundant duration, determining that the second duration module whose length exceeds the minimum length of the time gap is the third duration module; Align the end of the third duration module with the end of the target time interval; Connect the first portions of the remaining second duration modules except the third duration module in the second duration module to form a fourth duration module, and align the fourth duration module with the top of the target time interval; If the total duration is greater than or equal to the third redundant duration, the first priority allocation target is the second duration module of each layer that just fills the target time interval after the n+1th layer; The intervention timing of the first target robot-assisted task transfer is determined based on the allocation situation of each allocation layer, and the corresponding first target robot is scheduled to intervene in the auxiliary task transfer.

8. A surgical kit management method with intelligent control sorting and automatic packaging, characterized in that: include: Step 1: Automatically match the standard configuration of the package based on the input surgical requirements; Step 2: Control the intelligent sorting execution structure to sort the consumables required according to the standard configuration of the package; Step 3: After the required consumables are sorted, they are automatically packaged.

9. The surgical kit management method with intelligent control sorting and automatic packaging as claimed in claim 8, characterized in that: Also includes: Step 4: Verify the storage compliance of the inventory consumables based on the preset storage conditions of the inventory consumables and the real-time environmental status of the inventory consumables.

10. The surgical kit management method with intelligent control sorting and automatic packaging according to claim 8, characterized in that: Also includes: Step 5: Link with the hospital information system to obtain surgery scheduling information, and generate an input surgery demand waiting sequence based on the surgery scheduling information.

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